Package 'pkr' reference manual

Title:	Pharmacokinetics in R
Description:	Conduct a noncompartmental analysis as closely as possible to the most widely used commercial software. Some features are 1) CDISC SDTM terms 2) Automatic slope selection with the same criterion of WinNonlin(R) 3) Supporting both 'linear-up linear-down' and 'linear-up log-down' method 4) Interval(partial) AUCs with 'linear' or 'log' interpolation method * Reference: Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016. (ISBN:9198299107).
Authors:	Kyun-Seop Bae [aut], Jee Eun Lee [aut]
Maintainer:	Kyun-Seop Bae <[email protected]>
License:	GPL-3
Version:	0.1.3
Built:	2024-11-27 06:31:07 UTC
Source:	CRAN

Pharmacokinetics in R

Description

It conducts a noncompartmental analysis(NCA) as closely as possible to the most widely used commercial pharmacokinetic analysis software.

Details

The main functions are

NCA	     to perform NCA for many subjects.

IndiNCA  to perform NCA for one subject.

Author(s)

Kyun-Seop Bae <[email protected]>, Jee Eun Lee <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

# Theoph and Indometh data: dose in mg, conc in mg/L, time in h
NCA(Theoph, "Subject", "Time", "conc", dose=320, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
NCA(Theoph, "Subject", "Time", "conc", dose=320, iAUC=iAUC, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", iAUC=iAUC, uConc="mg/L")

# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, report="Text", uConc="mg/L"),
#            "Theoph_Linear_CoreOutput.txt")
# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, fit="Log", report="Text",
#            uConc="mg/L"), "Theoph_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", report="Text",
#            uConc="mg/L"), "Indometh_Bolus_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", fit="Log",
#            report="Text", uConc="mg/L"), "Indometh_Bolus_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            report="Text", uConc="mg/L"), "Indometh_Infusion_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            fit="Log", report="Text", uConc="mg/L"), "Indometh_Infusion_Log_CoreOutput.txt")

sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, concUnit="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        iAUC=iAUC, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", iAUC=iAUC, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, iAUC=iAUC, concUnit="mg/L")
# Theoph and Indometh data: dose in mg, conc in mg/L, time in h
NCA(Theoph, "Subject", "Time", "conc", dose=320, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
NCA(Theoph, "Subject", "Time", "conc", dose=320, iAUC=iAUC, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", iAUC=iAUC, uConc="mg/L")

# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, report="Text", uConc="mg/L"),
#            "Theoph_Linear_CoreOutput.txt")
# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, fit="Log", report="Text",
#            uConc="mg/L"), "Theoph_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", report="Text",
#            uConc="mg/L"), "Indometh_Bolus_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", fit="Log",
#            report="Text", uConc="mg/L"), "Indometh_Bolus_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            report="Text", uConc="mg/L"), "Indometh_Infusion_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            fit="Log", report="Text", uConc="mg/L"), "Indometh_Infusion_Log_CoreOutput.txt")

sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, concUnit="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        iAUC=iAUC, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", iAUC=iAUC, concUnit="mg/L")
sNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, iAUC=iAUC, concUnit="mg/L")

Calculate Area Under the Curve (AUC) and Area Under the first Moment Curve (AUMC) in a table format

Description

Calculate Area Under the Curve(AUC) and the first Moment Curve(AUMC) in two ways; 'linear trapezoidal method' or 'linear-up and log-down' method. Return a table of cumulative values.

Usage

AUC(x, y, down = "Linear")AUC(x, y, down = "Linear")

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC

Details

down="Linear" means linear trapezoidal rule with linear interpolation. down="Log" means linear-up and log-down method.

Value

Table with two columns, AUC and AUMC; the first column values are cumulative AUCs and the second column values cumulative AUMCs.

Author(s)

Kyun-Seop Bae <[email protected]>

References

Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. pp687-689. 2011.

Examples

AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")

Choose best fit slope for the log(y) and x regression by the criteria of adjusted R-square

Description

It sequentially fits (log(y) ~ x) from the last point of x to the previous points with at least 3 points. It chooses a slope the highest adjusted R-square. If the difference is less then 1e-4, it chooses longer slope.

Usage

BestSlope(x, y, adm = "Extravascular", TOL=1e-4)BestSlope(x, y, adm = "Extravascular", TOL=1e-4)

Arguments

`x`	vector values of x-axis, usually time
`y`	vector values of y-axis, usually concentration
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`TOL`	tolerance. See Phoneix WinNonlin 6.4 User's Guide p33 for the detail.

Details

Choosing the best terminal slope (y in log scale) in pharmacokinetic analysis is somewhat challenging, and it could vary by analysis performer. Pheonix WinNonlin chooses a slope with highest adjusted R-squared and the longest one. Difference of adjusted R-Squared less than TOL considered to be 0. This function uses ordinary least square method (OLS).

Value

`R2`	R-squared
`R2ADJ`	adjusted R-squared
`LAMZNPT`	number of points used for slope
`LAMZ`	negative of slope, lambda_z
`b0`	intercept of regression line
`CORRXY`	correlation of log(y) and x
`LAMZLL`	earliest x for lambda_z
`LAMZUL`	last x for lambda_z
`CLSTP`	predicted y value at last point, predicted concentration for the last time point

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"],
          adm="Bolus")
BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"],
          adm="Bolus")

Combine XPT files

Description

This function combines specified CDISC domain XPT files across the folders.

Usage

combXPT(folders, domain)combXPT(folders, domain)

Arguments

`folders`	where to find specified CDISC domain XPT files
`domain`	domain XPT files to be comined across the folders

Details

You need to designate only one CDISC domain name. You may specify one or more folders to find the domain XPT files.

Value

XPT

combined table

Author(s)

Kyun-Seop Bae <[email protected]>

Forest plot to compare NCA results

Description

This function compares NCA results usually from rNCA function

Usage

foreNCA(NCAres = "", PPTESTCD = "", PCTESTCD = "", title = "", ...)
foreNCA(NCAres = "", PPTESTCD = "", PCTESTCD = "", title = "", ...)

Arguments

`NCAres`	NCA results from rNCA function
`PPTESTCD`	CDISC SDTM PP domain Test Code to coompare
`PCTESTCD`	Molecular species to compare specified in PCTESTCD of CDISC SDTM PC domain
`title`	Title of the plot
`...`	further aguments to pass to the forestplot function

Details

This functio calls forestplot in forest package.

Value

Currently, this just plots.

Author(s)

Kyun-Seop Bae <[email protected]>

Noncompartmental Analysis for an Individual

Description

It performs a noncompartmental analysis with one subject data. This will be deprecated. Use sNCA() instead.

Usage

IndiNCA(x, y, dose = 0, fit = "Linear", adm = "Extravascular", dur = 0,
               report = "Table", iAUC = "", uTime = "h", uConc = "ug/L", uDose = "mg")IndiNCA(x, y, dose = 0, fit = "Linear", adm = "Extravascular", dur = 0,
               report = "Table", iAUC = "", uTime = "h", uConc = "ug/L", uDose = "mg")

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration
`dose`	administered dose for the subject
`fit`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	infusion duration for constant infusion, otherwise 0
`report`	either of `"Table"` or `"Text"` to specify the type of return value
`iAUC`	data.frame with three columns, "Name", "Start", "End" to specify the invervals for partial (interval) AUC
`uTime`	unit of time
`uConc`	unit of concentration
`uDose`	unit of dose

Details

This performs a noncompartmental analysis for a subject. It returns practically the same result with the most popular commercial software.

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at stead state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, uConc="mg/L")

IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        report="Text", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", report="Text", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, report="Text", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        iAUC=iAUC, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", iAUC=iAUC, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, iAUC=iAUC, uConc="mg/L")
IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, uConc="mg/L")

IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        report="Text", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", report="Text", uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, report="Text", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
IndiNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], dose=320,
        iAUC=iAUC, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Bolus", iAUC=iAUC, uConc="mg/L")
IndiNCA(Indometh[Indometh$Subject==1,"time"], Indometh[Indometh$Subject==1, "conc"], dose=25,
        adm="Infusion", dur=0.25, iAUC=iAUC, uConc="mg/L")

Calculate interval AUC

Description

It calculates interval AUC

Usage

IntAUC(x, y, t1, t2, Res, down = "Linear")IntAUC(x, y, t1, t2, Res, down = "Linear")

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration
`t1`	start time for AUC
`t2`	end time for AUC
`Res`	result from `IndiNCA` function
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC

Details

This calculates an interval (partial) AUC (from t1 to t2) with the given series of x and y. If t1 and/or t2 cannot be found within x vector, it interpolates according to the down option.

Value

return interval AUC value (scalar)

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

Res = sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], 
           dose=320, concUnit="mg/L")
IntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11, Res)
Res = sNCA(Theoph[Theoph$Subject==1,"Time"], Theoph[Theoph$Subject==1, "conc"], 
           dose=320, concUnit="mg/L")
IntAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], t1=0.5, t2=11, Res)

Interpolate y value

Description

It interpolates y value when a corresponding x value (xnew) does not exist within x vector

Usage

Interpol(x, y, xnew, Slope, b0, down = "Linear")Interpol(x, y, xnew, Slope, b0, down = "Linear")

Arguments

`x`	vector values of x-axis, usually time
`y`	vector values of y-axis, usually concentration
`xnew`	new x point to be interpolated, usually new time point
`Slope`	slope of regression log(y) ~ x
`b0`	y value of just left point of xnew
`down`	either of `"Linear"` or `"Log"` to indicate the way to interpolate

Details

This function interpolate y value, if xnew is not in x vector. If xnew is in x vector, it just returns the given x and y vector. This function usually is called by IntAUC function Returned vector is sorted in the order of increasing x values.

Value

new x and y vector containing xnew and ynew point

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

x = 10:1 + 0.1
y = -2*x + 40.2
Interpol(x, y, 1.5)
Interpol(x, y, 1.5, down="Log")
x = 10:1 + 0.1
y = -2*x + 40.2
Interpol(x, y, 1.5)
Interpol(x, y, 1.5, down="Log")

Area Under the Curve(AUC) and Area Under the first Moment Curve(AUMC) by linear trapezoidal method

Description

It calculates AUC and AUMC using linear trapezoidal method

Usage

LinAUC(x, y)LinAUC(x, y)

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration

Details

This function returns AUC and AUMC by linear trapezoidal method.

Value

`AUC`	area under the curve
`AUMC`	area under the first moment curve

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

LinAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # compare the last line
LinAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"]) # compare the last line

Load EX and PC domain files in folders

Description

This loads and returns EX and PC domain files in the specified folders

Usage

loadEXPC(folders)loadEXPC(folders)

Arguments

folders

folders where to find EX and PC domain files

Details

This reads EX and PC domain files in the specified folder. This calls readEX and readPC functions.

Value

`EX`	combined EX domain data
`PC`	combined PC doamin data

Author(s)

Kyun-Seop Bae <[email protected]>

Area Under the Curve(AUC) and Area Under the first Moment Curve(AUMC) by linear-up log-down method

Description

It calculates AUC and AUMC using linear-up log-down method

Usage

LogAUC(x, y)LogAUC(x, y)

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration

Details

This function returns AUC and AUMC by linear-up log-down method.

Value

`AUC`	area under the curve
`AUMC`	area under the first moment curve

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

LogAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
# Compare the last line with the above
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log") 
LogAUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
# Compare the last line with the above
AUC(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"], down="Log")

Noncompartmental analysis for a dataset with multiple subjects

Description

conduct noncompartmental analysis for many subjects in a data table

Usage

NCA(concData, id, Time, conc, trt="", fit = "Linear", dose = 0, 
           adm = "Extravascular", dur = 0, report = "Table", iAUC = "", 
           uTime = "h", uConc = "ug/L", uDose = "mg")NCA(concData, id, Time, conc, trt="", fit = "Linear", dose = 0, 
           adm = "Extravascular", dur = 0, report = "Table", iAUC = "", 
           uTime = "h", uConc = "ug/L", uDose = "mg")

Arguments

`concData`	name of data table containing time-concentration data of multiple subjects
`id`	column name for subject ID
`Time`	column name for the time
`conc`	column name for the concentration
`trt`	column name for the treatment code. This is useful for crossover study like bioequivalence trial.
`fit`	one of `"Linear"` or `"Log"` to indicate the way to calculate AUC
`dose`	administered dose. One should be careful for the unit. This can be a vector containing dose for each subject in order.
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	infusion duration for constant infusion, otherwise 0. This can be a vector containing values for each subject in order.
`report`	either of `"Table"` or `"Text"` to specify the type of return value
`iAUC`	data.frame with three columns, "Name", "Start", "End" to specify partial interval AUC
`uTime`	unit of time
`uConc`	unit of concentration
`uDose`	unit of dose

Details

This function calls IndiNCA repeatedly to do NCA for each subject. If you specify Report="Text", this function returns in free text format to be used in a report file.

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at stead state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.
Shargel L, Yu A. Applied Biopharmaceutics and Pharmacokinetics. 7th ed. 2015.
Rowland M, Tozer TN. Clinical Pharmacokinetics and Pharmacodynamics - Concepts and Applications. 4th ed. 2011.
Gibaldi M, Perrier D. Pharmacokinetics. 2nd ed. revised and expanded. 1982.

Examples

# Theoph and Indometh data: dose in mg, conc in mg/L, time in h
NCA(Theoph, "Subject", "Time", "conc", dose=320, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
NCA(Theoph, "Subject", "Time", "conc", dose=320, iAUC=iAUC, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", iAUC=iAUC, uConc="mg/L")

# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, report="Text", uConc="mg/L"),
#            "Theoph_Linear_CoreOutput.txt")
# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, fit="Log", report="Text", 
#            uConc="mg/L"), "Theoph_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", report="Text", 
#            uConc="mg/L"), "Indometh_Bolus_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", fit="Log",
#            report="Text", uConc="mg/L"), "Indometh_Bolus_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            report="Text", uConc="mg/L"), "Indometh_Infusion_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            fit="Log", report="Text", uConc="mg/L"), "Indometh_Infusion_Log_CoreOutput.txt")
# Theoph and Indometh data: dose in mg, conc in mg/L, time in h
NCA(Theoph, "Subject", "Time", "conc", dose=320, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", uConc="mg/L")

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24)) ; iAUC
NCA(Theoph, "Subject", "Time", "conc", dose=320, iAUC=iAUC, uConc="mg/L")
NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", iAUC=iAUC, uConc="mg/L")

# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, report="Text", uConc="mg/L"),
#            "Theoph_Linear_CoreOutput.txt")
# writeLines(NCA(Theoph, "Subject", "Time", "conc", dose=320, fit="Log", report="Text", 
#            uConc="mg/L"), "Theoph_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", report="Text", 
#            uConc="mg/L"), "Indometh_Bolus_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Bolus", fit="Log",
#            report="Text", uConc="mg/L"), "Indometh_Bolus_Log_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            report="Text", uConc="mg/L"), "Indometh_Infusion_Linear_CoreOutput.txt")
# writeLines(NCA(Indometh, "Subject", "time", "conc", dose=25, adm="Infusion", dur=0.25,
#            fit="Log", report="Text", uConc="mg/L"), "Indometh_Infusion_Log_CoreOutput.txt")

NCA of SDTM data for single subject

Description

This performs Noncompartmental Analysis(NCA) for only one subject from the CDISC EX and PC domain.

Usage

NCA0(EX0, PC0, fit="Linear")NCA0(EX0, PC0, fit="Linear")

Arguments

`EX0`	Data of one subject from EX domain
`PC0`	Data of one subject from PC domain
`fit`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC

Details

This calls IndiNCA function. This is called by rNCA function.

Value

This returns NCA results vector.

Author(s)

Kyun-Seop Bae <[email protected]>

NCA output to pdf file

Description

This output NCA result in a pdf file.

Usage

pdfNCA(fileName = "Temp-NCA.pdf", concData, colSubj = "Subject", colTime = "Time", 
       colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", 
       timeUnit = "h", concUnit = "ug/L", down="Linear", MW = 0)
pdfNCA(fileName = "Temp-NCA.pdf", concData, colSubj = "Subject", colTime = "Time", 
       colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", 
       timeUnit = "h", concUnit = "ug/L", down="Linear", MW = 0)

Arguments

`fileName`	file name to save
`concData`	concentration data table
`colSubj`	column name for subject ID
`colTime`	column name for time
`colConc`	column name for concentration
`dose`	administered dose
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	duration of infusion
`doseUnit`	unit of dose
`timeUnit`	unit of time
`concUnit`	unit of concentration
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`MW`	molecular weight of drug

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at stead state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

#pdfNCA(fileName="NCA-Theoph.pdf", Theoph, colSubj="Subject", colTime="Time", 
#       colConc="conc", dose=320, doseUnit="mg", timeUnit="h", concUnit="mg/L")
#pdfNCA(fileName="NCA-Indometh.pdf", Indometh, colSubj="Subject", colTime="time", 
#       colConc="conc", adm="Infusion", dur=0.5, dose=25, doseUnit="mg", 
#       timeUnit="h", concUnit="mg/L")
#pdfNCA(fileName="NCA-Theoph.pdf", Theoph, colSubj="Subject", colTime="Time", 
#       colConc="conc", dose=320, doseUnit="mg", timeUnit="h", concUnit="mg/L")
#pdfNCA(fileName="NCA-Indometh.pdf", Indometh, colSubj="Subject", colTime="time", 
#       colConc="conc", adm="Infusion", dur=0.5, dose=25, doseUnit="mg", 
#       timeUnit="h", concUnit="mg/L")

Plot best fit slope

Description

Automatically select best fit slope for the given x(usually time) and log(y)(usually concentration) values.

Usage

plotFit(concData, id, Time, conc, mol = "", adm = "Extravascular", ID = "", Mol = "")
plotFit(concData, id, Time, conc, mol = "", adm = "Extravascular", ID = "", Mol = "")

Arguments

`concData`	name of data table containing time-concentration data of multiple subjects
`id`	column name for subject ID
`Time`	column name for the time
`conc`	column name for the concentration
`mol`	column name for molecular species
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`ID`	Subject ID for this plot
`Mol`	the name of molecular species to see

Details

Find the best fit slope then plot it. Currently this function uses ordinary least square method(OLS) only. This function calles BestSlope function.

Value

`R2`	R-squared
`R2ADJ`	adjusted R-squared
`LAMZNPT`	number of points used for slope
`LAMZ`	negative of slope, lambda_z
`b0`	intercept of regression line
`CORRXY`	correlation of log(y) and x
`LAMZLL`	earliest x for lambda_z
`LAMZUL`	last x for lambda_z
`CLSTP`	predicted y value at last point, predicted concentration for the last time point

Author(s)

Jee Eun Lee <[email protected]>

Examples

plotFit(Theoph, "Subject", "Time", "conc", ID="1")
plotFit(Indometh, "Subject", "time", "conc", adm="Bolus", ID="1")
plotFit(Theoph, "Subject", "Time", "conc", ID="1")
plotFit(Indometh, "Subject", "time", "conc", adm="Bolus", ID="1")

Plot concentration vs. time curve for individuals and collectively.

Description

Generates individual and superposed concentration vs. time curve and save it in pdf files.

Usage

plotPK(concData, id, Time, conc, unitTime = "hr", unitConc = "ng/mL", trt = "", 
       fit = "Linear", dose = 0, adm = "Extravascular", dur = 0, outdir = "Output")
plotPK(concData, id, Time, conc, unitTime = "hr", unitConc = "ng/mL", trt = "", 
       fit = "Linear", dose = 0, adm = "Extravascular", dur = 0, outdir = "Output")

Arguments

`concData`	name of data table containing time-concentration data of multiple subjects
`id`	column name for subject ID
`Time`	column name for the time
`conc`	column name for the concentration
`unitTime`	unit for the time
`unitConc`	unit for the concentration
`trt`	column name for the treatment code. This is useful for crossover study like bioequivalence trial.
`fit`	one of `"Linear"` or `"Log"` to indicate the way to calculate AUC
`dose`	administered dose. One should be careful for the unit. This can be a vector containing dose for each subject in order.
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	infusion duration for constant infusion, otherwise 0. This can be a vector containing values for each subject in order.
`outdir`	name of the folder to be used for the output files

Details

This function generates plots for individual and summary concentration vs. time curve. This function calles NCA().

Value

This function saves pdf files and tiff files in the outdir folder.

Author(s)

Jee Eun Lee <[email protected]>

Examples

# plotPK(Theoph, "Subject", "Time", "conc", unitTime="hr", unitConc="mg/L", dose=320)
# plotPK(Indometh, "Subject", "time", "conc", unitTime="hr", unitConc="mg/L", adm="Bolus", dose=25)
# plotPK(Theoph, "Subject", "Time", "conc", unitTime="hr", unitConc="mg/L", dose=320)
# plotPK(Indometh, "Subject", "time", "conc", unitTime="hr", unitConc="mg/L", adm="Bolus", dose=25)

Read EX domain files

Description

This reads EX domain files from the specified folders.

Usage

readEX(folders)
readEX(folders)

Arguments

folders

folders where to find EX doamin files

Details

This calls combXPT function. This is called by loadEXPC function.

Value

This returns combined table of EX doamin.

Author(s)

Kyun-Seop Bae <[email protected]>

Read PC domain files

Description

This reads PC domain files from the specified folders.

Usage

readPC(folders)
readPC(folders)

Arguments

folders

folders where to find PC doamin files

Details

This calls combXPT function. This is called by loadEXPC function.

Value

This returns combined table of PC doamin.

Author(s)

Kyun-Seop Bae <[email protected]>

Do NCA for review

Description

This performs NCA from the CDISC EX and PC datasets.

Usage

rNCA(ex, pc, study = "", trt = "", id = "", analyte = "", 
     codeBQL = c("< 0", "<0", "NQ", "BLQ", "BQL", "BQoL", "<LOQ"), 
     fit="Linear", MinPoints = 5)
rNCA(ex, pc, study = "", trt = "", id = "", analyte = "", 
     codeBQL = c("< 0", "<0", "NQ", "BLQ", "BQL", "BQoL", "<LOQ"), 
     fit="Linear", MinPoints = 5)

Arguments

`ex`	EX domain data, usually from the `loadEXPC`
`pc`	PC domain data, usually form the `loadEXPC`
`study`	vector of study names in EX and PC domain to do NCA
`trt`	vector of treatment names in EXTRT to do NCA
`id`	vector of subject IDs in USUBJID to do NCA
`analyte`	vector of molecular species in PCTESTCD to do NCA
`codeBQL`	symbols of below the quantitation limit
`fit`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`MinPoints`	minimum number of sampling points for NCA

Details

This calls NCA0. Results of this can be further processed by foreNCA to plot and compare between studies and dose groups.

Value

This returns a table of NCA results

Author(s)

Kyun-Seop Bae <[email protected]>

Round Half Away from Zero

Description

This is an ordinary rounding function, so called round half away from zero

Usage

Round(x, n = 0)Round(x, n = 0)

Arguments

`x`	numeric to be rounded
`n`	indicating decimal digits

Details

The function round in R base rounds to the even number, i.e. round(0.5) is 0 not 1. If you want rounding 0.5 be 1, you can use this Round function. This function is for the consistency with other software like MS-Excel, SAS.

Value

ordinarily rounded value

Author(s)

Kyun-Seop Bae <[email protected]>

References

See wikipedia subject "Rounding"

Examples

(x = 1:10 - 0.5)
Round(x)
round(x) # compare with the above
(x = 1:10 - 0.5)
Round(x)
round(x) # compare with the above

NCA Report Configuation Table

Description

Contains the names and order of colum of return table/text by IndiNCA and NCA functions

Usage

RptCfgRptCfg

Format

A data frame with 48 observations on the following 10 variables.

PPTESTCD: a character vector of CDISC SDTM PPTESTCD
SYNONYM: a character vector of CDISC SDTM PPTESTCD Synonym
NCI: a character vector of NCI peferred terms
WNL: a character vector of WinNonlin(R) software variables
ExtravascularDefault: a numeric vector of ordering in report for extravascular administration, Zero means exclusion in the report.
ExtravascularWNL: a numeric vector of WinNonlin(R) style ordering in report for extravascular administration, Zero means exclusion in the report.
BolusDefault: a numeric vector of ordering in report for extravascular administration, Zero means exclusion in the report.
BolusWNL: a numeric vector of WinNonlin(R) style ordering in report for extravascular administration, Zero means exclusion in the report.
InfusionDefault: a numeric vector of ordering in report for extravascular administration, Zero means exclusion in the report.
InfusionWNL: a numeric vector of WinNonlin(R) style ordering in report for extravascular administration, Zero means exclusion in the report.

Details

This table should exist in pkr package. User can edit this table for shaping the report in one's own style.

NCA output to rtf file

Description

This output NCA result in a rtf file.

Usage

rtfNCA(fileName = "Temp-NCA.rtf", concData, colSubj = "Subject", colTime = "Time", 
       colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", 
       timeUnit = "h", concUnit = "ug/L", down="Linear", MW = 0)
rtfNCA(fileName = "Temp-NCA.rtf", concData, colSubj = "Subject", colTime = "Time", 
       colConc = "conc", dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", 
       timeUnit = "h", concUnit = "ug/L", down="Linear", MW = 0)

Arguments

`fileName`	file name to save
`concData`	concentration data table
`colSubj`	column name for subject ID
`colTime`	column name for time
`colConc`	column name for concentration
`dose`	administered dose
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	duration of infusion
`doseUnit`	unit of dose
`timeUnit`	unit of time
`concUnit`	unit of concentration
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`MW`	molecular weight of drug

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at stead state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

#rtfNCA(fileName="NCA-Theoph.rtf", Theoph, colSubj="Subject", colTime="Time", 
#       colConc="conc", dose=320, doseUnit="mg", timeUnit="h", concUnit="mg/L")
#rtfNCA(fileName="NCA-Indometh.rtf", Indometh, colSubj="Subject", colTime="time", 
#       colConc="conc", adm="Infusion", dur=0.5, dose=25, doseUnit="mg", 
#       timeUnit="h", concUnit="mg/L")
#rtfNCA(fileName="NCA-Theoph.rtf", Theoph, colSubj="Subject", colTime="Time", 
#       colConc="conc", dose=320, doseUnit="mg", timeUnit="h", concUnit="mg/L")
#rtfNCA(fileName="NCA-Indometh.rtf", Indometh, colSubj="Subject", colTime="time", 
#       colConc="conc", adm="Infusion", dur=0.5, dose=25, doseUnit="mg", 
#       timeUnit="h", concUnit="mg/L")

Get the Slope of regression log(y) ~ x

Description

It calculates the slope with linear regression of log(y) ~ x

Usage

Slope(x, y)Slope(x, y)

Arguments

`x`	vector values of independent variable, usually time
`y`	vector values of dependent variable, usually concentration

Details

With time-concentration curve, you frequently need to estimate slope in log(concentration) ~ time. This function is usually called by BestSlope function and you seldom need to call this function directly.

Value

`R2`	R-squared
`R2ADJ`	adjusted R-squared
`LAMZNPT`	number of points used for slope
`LAMZ`	negative of slope, lambda_z
`b0`	intercept of regression line
`CORRXY`	correlation of log(y) and x
`LAMZLL`	earliest x for lambda_z
`LAMZUL`	last x for lambda_z
`CLSTP`	predicted y value at last point, predicted concentration for the last time point

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])
Slope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"])

Simplest NCA

Description

This is the work-horse function for NCA.

Usage

sNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
     concUnit = "ug/L", iAUC = "", down = "Linear", MW = 0, returnNA = TRUE)
sNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
     concUnit = "ug/L", iAUC = "", down = "Linear", MW = 0, returnNA = TRUE)

Arguments

`x`	usually time
`y`	usually concentration
`dose`	given amount
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	duration of infusion
`doseUnit`	unit of dose
`timeUnit`	unit of time
`concUnit`	unit of concentration
`iAUC`	interval AUCs to calculate
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`MW`	molecular weight of the drug
`returnNA`	if `returnNA` is `TRUE`, it returns NA values also.

Details

This will replace IndiNCA.

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at steady state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

References

Gabrielsson J, Weiner D. Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications. 5th ed. 2016.

Examples

# For one subject
x = Theoph[Theoph$Subject=="1","Time"]
y = Theoph[Theoph$Subject=="1","conc"]

sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")
sNCA(x, y, dose=320, concUnit="mg/L", returnNA=FALSE)

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24))
sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC)

MW = 180.164 # Molecular weight of theophylline

sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h")
sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h", MW=MW)
sNCA(x, y, dose=320/MW, doseUnit="mmol", concUnit="mg/L", timeUnit="h", MW=MW)
sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW)

sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW, 
     returnNA=FALSE)
sNCA(x, y/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW, returnNA=FALSE)
sNCA(x, y/MW, dose=as.numeric(NA), doseUnit="mmol", concUnit="mmol/L", timeUnit="h", 
     MW=MW, returnNA=FALSE)

sNCA(x, y, dose=320, concUnit="mg/L", timeUnit="hr")
sNCA(x*60, y, dose=320, concUnit="mg/L", timeUnit="min")
# For one subject
x = Theoph[Theoph$Subject=="1","Time"]
y = Theoph[Theoph$Subject=="1","conc"]

sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")
sNCA(x, y, dose=320, concUnit="mg/L", returnNA=FALSE)

iAUC = data.frame(Name=c("AUC[0-12h]","AUC[0-24h]"), Start=c(0,0), End=c(12,24))
sNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h", iAUC=iAUC)

MW = 180.164 # Molecular weight of theophylline

sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h")
sNCA(x, y/MW, dose=320, doseUnit="mg", concUnit="mmol/L", timeUnit="h", MW=MW)
sNCA(x, y, dose=320/MW, doseUnit="mmol", concUnit="mg/L", timeUnit="h", MW=MW)
sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW)

sNCA(x, y/MW, dose=320/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW, 
     returnNA=FALSE)
sNCA(x, y/MW, doseUnit="mmol", concUnit="mmol/L", timeUnit="h", MW=MW, returnNA=FALSE)
sNCA(x, y/MW, dose=as.numeric(NA), doseUnit="mmol", concUnit="mmol/L", timeUnit="h", 
     MW=MW, returnNA=FALSE)

sNCA(x, y, dose=320, concUnit="mg/L", timeUnit="hr")
sNCA(x*60, y, dose=320, concUnit="mg/L", timeUnit="min")

Table output NCA

Description

do multiple NCA and returns a result table.

Usage

tblNCA(concData, key = "Subject", colTime = "Time", colConc = "conc", dose = 0, 
       adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
       concUnit = "ug/L", down = "Linear", MW = 0, returnNA = FALSE)
tblNCA(concData, key = "Subject", colTime = "Time", colConc = "conc", dose = 0, 
       adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
       concUnit = "ug/L", down = "Linear", MW = 0, returnNA = FALSE)

Arguments

`concData`	concentration data table
`key`	column names of concData to be shown at the output table
`colTime`	column name for time
`colConc`	column name for concentration
`dose`	administered dose
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	duration of infusion
`doseUnit`	unit of dose
`timeUnit`	unit of time
`concUnit`	unit of concentration
`down`	method to calculate AUC, `"Linear"` or `"Log"`
`MW`	molecular weight of drug
`returnNA`	if `returnNA` is `TRUE`, it returns NA values also.

Value

Basically same with sNCA

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

tblNCA(Theoph, key="Subject", dose=320, concUnit="mg/L")
tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, 
       adm="Infusion", dur=0.5, concUnit="mg/L")
tblNCA(Theoph, key="Subject", dose=320, concUnit="mg/L")
tblNCA(Indometh, key="Subject", colTime="time", colConc="conc", dose=25, 
       adm="Infusion", dur=0.5, concUnit="mg/L")

Text output of NCA for one subject

Description

This is the text form output.

Usage

txtNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
       concUnit = "ug/L", iAUC = "", down="Linear", MW = 0, returnNA = FALSE)
txtNCA(x, y, dose = 0, adm = "Extravascular", dur = 0, doseUnit = "mg", timeUnit = "h", 
       concUnit = "ug/L", iAUC = "", down="Linear", MW = 0, returnNA = FALSE)

Arguments

`x`	usually time
`y`	usually concentration
`dose`	given amount
`adm`	one of `"Bolus"` or `"Infusion"` or `"Extravascular"` to indicate drug administration mode
`dur`	duration of infusion
`doseUnit`	unit of dose
`timeUnit`	unit of time
`concUnit`	unit of concentration
`iAUC`	interval AUCs to calculate
`down`	either of `"Linear"` or `"Log"` to indicate the way to calculate AUC and AUMC
`MW`	molecular weight of the drug
`returnNA`	if `returnNA` is `TRUE`, it returns NA values also.

Value

`CMAX`	maximum concentration, Cmax
`CMAXD`	dose normalized Cmax, CMAX / Dose, Cmax / Dose
`TMAX`	time of maximum concentration, Tmax
`TLAG`	time to observe the first non-zero concentration, for extravascular administration only
`CLST`	last positive concentration observed, Clast
`CLSTP`	last positive concentration predicted, Clast_pred
`TLST`	time of last positive concentration, Tlast
`LAMZHL`	half-life by lambda z, ln(2)/LAMZ
`LAMZ`	lambda_z negative of best fit terminal slope
`LAMZLL`	earliest time for LAMZ
`LAMZUL`	last time for LAMZ
`LAMZNPT`	number of points for LAMZ
`CORRXY`	correlation of log(concentration) and time
`R2`	R-squared
`R2ADJ`	R-squared adjusted
`C0`	back extrapolated concentration at time 0, for bolus intravascular administration only
`AUCLST`	AUC from 0 to TLST
`AUCALL`	AUC using all the given points, including trailing zero concentrations
`AUCIFO`	AUC infinity observed
`AUCIFOD`	AUCIFO / Dose
`AUCIFP`	AUC infinity predicted using CLSTP instead of CLST
`AUCIFPD`	AUCIFP / Dose
`AUCPEO`	AUC % extrapolation observed
`AUCPEP`	AUC % extrapolated for AUCIFP
`AUCPBEO`	AUC % back extrapolation observed, for bolus IV administration only
`AUCPBEP`	AUC % back extrapolation predicted with AUCIFP, for bolus IV administration only
`AUMCLST`	AUMC to the TLST
`AUMCIFO`	AUMC infinity observed using CLST
`AUMCIFP`	AUMC infinity determined by CLSTP
`AUMCPEO`	AUMC % extrapolated observed
`AUMCPEP`	AUMC % extrapolated predicted
`MRTIVLST`	mean residence time (MRT) to TLST, for intravascular administration
`MRTIVIFO`	mean residence time (MRT) infinity using CLST, for intravascular administration
`MRTIVIFP`	mean residence time (MRT) infinity using CLSTP, for intravascular administration
`MRTEVLST`	mean residence time (MRT) to TLST, for extravascular administration
`MRTEVIFO`	mean residence time (MRT) infinity using CLST, for extravascular administration
`MRTEVIFP`	mean residence time (MRT) infinity using CLSTP, for extravascular administration
`VZO`	volume of distribution determined by LAMZ and AUCIFO, for intravascular administration
`VZP`	volume of distribution determined by LAMZ and AUCIFP, for intravascular administration
`VZFO`	VZO for extravascular administration, VZO/F, F is bioavailability
`VZFP`	VZP for extravascular administration, VZP/F, F is bioavailability
`CLO`	clearance using AUCIFO, for intravascular administration
`CLP`	clearance using AUCIFP, for intravascular administration
`CLFO`	CLO for extravascular administration, CLO/F, F is bioavailability
`CLFP`	CLP for extravascular administration, CLP/F, F is bioavailability
`VSSO`	volume of distribution at steady state using CLST, for intravascular administration only
`VSSP`	volume of distribution at stead state using CLSTP, for intravascular administration only

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

# For one subject
txtNCA(Theoph[Theoph$Subject=="1","Time"], Theoph[Theoph$Subject=="1","conc"], 
       dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")

# or equivalently
x = Theoph[Theoph$Subject=="1","Time"]
y = Theoph[Theoph$Subject=="1","conc"]
txtNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")

# For all subjects
IDs = sort(as.numeric(unique(Theoph[,"Subject"])))
nID = length(IDs)
Res = vector()
for (i in 1:nID) {
  tRes = txtNCA(Theoph[Theoph[,"Subject"]==IDs[i],"Time"], 
                Theoph[Theoph[,"Subject"]==IDs[i],"conc"], 
                dose=320, concUnit="mg/L", returnNA=FALSE)
  tRes = c(paste("ID =", IDs[i]), tRes, "")
  Res = c(Res, tRes)
}
Res
# For one subject
txtNCA(Theoph[Theoph$Subject=="1","Time"], Theoph[Theoph$Subject=="1","conc"], 
       dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")

# or equivalently
x = Theoph[Theoph$Subject=="1","Time"]
y = Theoph[Theoph$Subject=="1","conc"]
txtNCA(x, y, dose=320, doseUnit="mg", concUnit="mg/L", timeUnit="h")

# For all subjects
IDs = sort(as.numeric(unique(Theoph[,"Subject"])))
nID = length(IDs)
Res = vector()
for (i in 1:nID) {
  tRes = txtNCA(Theoph[Theoph[,"Subject"]==IDs[i],"Time"], 
                Theoph[Theoph[,"Subject"]==IDs[i],"conc"], 
                dose=320, concUnit="mg/L", returnNA=FALSE)
  tRes = c(paste("ID =", IDs[i]), tRes, "")
  Res = c(Res, tRes)
}
Res

Disply CDISC standard units and multiplied factor of NCA results

Description

It displays CDISC PP output units and multiplication factor for them.

Usage

Unit(code = "", timeUnit = "h", concUnit = "ng/mL", doseUnit = "mg", MW = 0)
Unit(code = "", timeUnit = "h", concUnit = "ng/mL", doseUnit = "mg", MW = 0)

Arguments

`code`	vector of PPTESTCD
`timeUnit`	unit of time
`concUnit`	unit of concentration
`doseUnit`	unit of dose
`MW`	molecular weight of drug

Value

`row names`	PPTESTCD
`Unit`	unit
`Factor`	internal mulitpilcation factor

Author(s)

Kyun-Seop Bae <[email protected]>

Examples

Unit(concUnit="ug/L", doseUnit="mg")
Unit(concUnit="ng/L", doseUnit="mg")

Unit(concUnit="umol/L", doseUnit="mmol")
Unit(concUnit="nmol/L", doseUnit="mmol")

Unit(concUnit="mmol/L", doseUnit="mg", MW=500)
Unit(concUnit="umol/L", doseUnit="mg", MW=500)
Unit(concUnit="nmol/L", doseUnit="mg", MW=500)
Unit(concUnit="nmol/mL", doseUnit="mg", MW=500)

Unit(concUnit="ug/L", doseUnit="mmol", MW=500)
Unit(concUnit="ug/L", doseUnit="mol", MW=500)
Unit(concUnit="ng/L", doseUnit="mmol", MW=500)
Unit(concUnit="ng/mL", doseUnit="mmol", MW=500)

Unit(concUnit="nmol/L", doseUnit="mg")
Unit(concUnit="ug/L", doseUnit="mmol")
Unit(concUnit="ug/L", doseUnit="mg")
Unit(concUnit="ng/L", doseUnit="mg")

Unit(concUnit="umol/L", doseUnit="mmol")
Unit(concUnit="nmol/L", doseUnit="mmol")

Unit(concUnit="mmol/L", doseUnit="mg", MW=500)
Unit(concUnit="umol/L", doseUnit="mg", MW=500)
Unit(concUnit="nmol/L", doseUnit="mg", MW=500)
Unit(concUnit="nmol/mL", doseUnit="mg", MW=500)

Unit(concUnit="ug/L", doseUnit="mmol", MW=500)
Unit(concUnit="ug/L", doseUnit="mol", MW=500)
Unit(concUnit="ng/L", doseUnit="mmol", MW=500)
Unit(concUnit="ng/mL", doseUnit="mmol", MW=500)

Unit(concUnit="nmol/L", doseUnit="mg")
Unit(concUnit="ug/L", doseUnit="mmol")

Package 'pkr'

Help Index

Pharmacokinetics in R

Description

Details

Author(s)

References

Examples

Calculate Area Under the Curve (AUC) and Area Under the first Moment Curve (AUMC) in a table format

Description

Usage

Arguments

Details

Value

Author(s)

References

See Also

Examples

Choose best fit slope for the log(y) and x regression by the criteria of adjusted R-square

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Combine XPT files

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Forest plot to compare NCA results

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Noncompartmental Analysis for an Individual

Description

Usage

Arguments

Details

Value

Author(s)

References

See Also

Examples

Calculate interval AUC

Description

Usage

Arguments

Details

Value

Author(s)

References

See Also

Examples

Interpolate y value

Description

Usage

Arguments

Details

Value

Author(s)

See Also

Examples

Area Under the Curve(AUC) and Area Under the first Moment Curve(AUMC) by linear trapezoidal method

Description

Usage

Arguments

Details

Value

Author(s)

References